Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD).
Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD).
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等位基因频率偏差 (AFD) 作为预测肺腺癌 (LUAD) 总生存率的新预后模型
DOI：
10.1186/s12935-021-02127-z
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发表时间：
2021-08-26
影响因子：
5.8
通讯作者：
Liu Q
中科院分区：
文献类型：
--
作者：
Al-Dherasi A;Liao Y;Al-Mosaib S;Hua R;Wang Y;Yu Y;Zhang Y;Zhang X;Jalayta R;Mousa H;Al-Danakh A;Alnadari F;Almoiliqy M;Baldi S;Shi L;Lv D;Li Z;Liu Q
肺腺癌（LUAD）仍然是世界上最著名的侵袭性恶性肿瘤之一，死亡率高。分子生物学分析和生物信息学是非常重要的，因为它们最近在各种生物标志物的鉴定和预测LUAD患者生存的研究中占据了很大的领域。在我们的研究中，我们试图通过开发一种新的算法来计算等位基因频率偏差（AFD），从而确定一种新的预后模型，这反过来可能有助于LUAD的早期诊断和临床结果预测。首先，开发了一种利用全外显子组测序（WES）数据集计算AFD的新算法。然后测量102例患者的AFD，并采用Kaplan-Meier分析、受试者工作特征（ROC）曲线和曲线下面积（AUC）评估AFD的预测能力。最后，进行多变量cox回归分析，以评估AFD作为独立预后工具的独立性。Kaplan-Meier分析显示，训练组的AFD有效地将LUAD患者分为高AFD值和低AFD值风险组（风险比HR = 1.125, 95%可信区间CI 1.001-1.26, p = 0.04）。此外，高afd值组患者的总生存期（OS）明显短于低afd值组，两组患者的死亡风险分别高42.8%和低10%（死亡HR = 1.10; 95% CI 1.01-1.2, p = 0.03）。验证组的结果相似（HR = 4.62, 95% CI 1.22-17.4, p = 0.02）， afd值高组和低组患者的死亡风险分别为41.6%和5.5%。单因素和多变量cox回归分析表明，AFD是LUAD患者的独立预后模型。训练组和验证组的5年生存AUC分别为0.712和0.86。AFD被认为是一种新的独立预后模型，可以为医生提供预后工具并有助于治疗决策。在线版本包含补充材料，可在10.1186/s12935-021-02127-z获得。
Lung adenocarcinoma (LUAD) remains one of the world’s most known aggressive malignancies with a high mortality rate. Molecular biological analysis and bioinformatics are of great importance as they have recently occupied a large area in the studies related to the identification of various biomarkers to predict survival for LUAD patients. In our study, we attempted to identify a new prognostic model by developing a new algorithm to calculate the allele frequency deviation (AFD), which in turn may assist in the early diagnosis and prediction of clinical outcomes in LUAD. First, a new algorithm was developed to calculate AFD using the whole-exome sequencing (WES) dataset. Then, AFD was measured for 102 patients, and the predictive power of AFD was assessed using Kaplan–Meier analysis, receiver operating characteristic (ROC) curves, and area under the curve (AUC). Finally, multivariable cox regression analyses were conducted to evaluate the independence of AFD as an independent prognostic tool. The Kaplan–Meier analysis showed that AFD effectively segregated patients with LUAD into high-AFD-value and low-AFD-value risk groups (hazard ratio HR = 1.125, 95% confidence interval CI 1.001–1.26, p = 0.04) in the training group. Moreover, the overall survival (OS) of patients who belong to the high-AFD-value group was significantly shorter than that of patients who belong to the low-AFD-value group with 42.8% higher risk and 10% lower risk of death for both groups respectively (HR for death = 1.10; 95% CI 1.01–1.2, p = 0.03) in the training group. Similar results were obtained in the validation group (HR = 4.62, 95% CI 1.22–17.4, p = 0.02) with 41.6%, and 5.5% risk of death for patients who belong to the high and low-AFD-value groups respectively. Univariate and multivariable cox regression analyses demonstrated that AFD is an independent prognostic model for patients with LUAD. The AUC for 5-year survival were 0.712 and 0.86 in the training and validation groups, respectively. AFD was identified as a new independent prognostic model that could provide a prognostic tool for physicians and contribute to treatment decisions. The online version contains supplementary material available at 10.1186/s12935-021-02127-z.
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影响因子：
4.8
作者：
Talvitie, Eva-Maria;Vilhonen, Heikki;Taimen, Pekka
通讯作者：
Taimen, Pekka
影响因子：
50.5
作者：
Crino, L.;Weder, W.;Felip, E.
通讯作者：
Felip, E.
DOI：
10.1093/bioinformatics/btp698
发表时间：
2010-03-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Li H;Durbin R
通讯作者：
Durbin R
影响因子：
20.4
作者：
Sawabata, Noriyoshi;Asamura, Hisao;Fujii, Yoshitaka
通讯作者：
Fujii, Yoshitaka
影响因子：
30.8
作者：
Samstein, Robert M.;Lee, Chung-Han;Morris, Luc G. T.
通讯作者：
Morris, Luc G. T.